Benefits of AI in Software Development and Product Building

Artificial Intelligence (AI) software and technology could be widely used in different industries and in businesses of any size. Manufacturing, customer service, call center, marketing, supply chain, and many more companies’ departments certainly can benefit from AI in software development.

There are several AI definitions coined through the years, as the concept of machines being able to think and act humanly reaches the 50s. This bold idea originated with Alan Turing’s work “Computing Machinery and Intelligence,” where he asked, “Can machines think?” kicking off the whole area of in-depth computer science study.

From that point, Artificial Intelligence had never stopped heating the imagination, causing a lot of inflated expectations and vast, exaggerated anxiety. Many evangelists of this emerging technology see only advantages in omniscient personal assistants, recommendation engines, and ranking scores, and those who are deeply upset with AI solutions stealing our jobs or driving our cars. As always, in the case of any emerging technologies, the truth is far from these Hollywood-like scenarios, though.

Artificial Intelligence is already here, reading our emails, listening to our conversations, and recognizing our faces, and it is nothing like a tasty piece for Silicon Valley VC. It is a must-have for any business innovation, as its primary goal is to improve business efficiency no matter how we define it.

So, what Artificial Intelligence is?

Today it is considered an umbrella term for the entire field of computer science that aims to mimic the human way of problem-solving and copy (and upgrade) the decision-making process. Artificial intelligence includes the sub-sets, from which the most common is Machine Learning and Deep Learning, as they cover the origin definition the most. Machine and Deep learning models make predictions or classifications based on input data.

However, that was not all. Artificial Intelligence covers a variety of specific AI-driven solutions that can be applied to manage different areas of business processes.

Computer Vision

Our team builds innovative applications and products by integrating computer vision services with other systems like POS, ERP, and diagnostic software. It is used to detect anomalies in shopping centers, track quality in production lines, analyze medical images, identify products on shelves and analyze people and their demographics on social media.

AI software development experts in Addepto have outstanding experience in building customized computer vision applications with advanced components based on neural networks such as object classification, feature recognition, image segmentation, pattern recognition, object detection, background segmentation, and emotion detection. Those solutions help to solve complex business challenges in different industries.

Natural Language Processing

Natural Language Processing (NLP) technology is becoming essential for every modern company which aims to gain a competitive advantage in their operations and customer service.

Addepto AI team has proven experience in building AI software based on NLP algorithms. This software includes chatbots, intelligent search systems, sentiment analysis, document summarization and understanding, compliance monitoring, recruiting, and text analysis on unstructured and semi-structured data.

Predictive Analytics

Predictive analytics includes AI solutions and software that helps you to understand customer behavior, and helps to steer your business in the right direction. Predictive analytics solutions are built for predicting and preventing customer churn, detecting anomalies in your business, to segment your customers into appropriate groups and clusters, predicting and optimizing your customer’s lifetime value, and predicting demand to optimize inventory and plan resources.

Recommendation and search engines

In the modern world providing users with a personalized experience is virtually a must. They adore feeling special and understanding that someone takes care of them.

That is why many companies turned to Addepto with custom recommendation engine requirements. Recommendation and smart search engines simply show that your website, app, or online store is personalized for every particular customer.

This is how the product recommendation system influences your customers to stay loyal, while more and more users join your service.

Speech analysis

Some modern applications require more advanced solutions to acquire new customers and improve their satisfaction. Some of the solutions that could be implemented into your mobile or web app are audio analysis and voice recognition based on AI solutions.

Addepto has experience in building voice recognition and analysis apps for similarity search for audio files, audio recommendation, indexing audio collections, speech-to-text, and text-to-speech systems, speech processing, and synthesis.

Optimization system

Optimization system has a goal to find the maximum or minimum value of some target function. Our team implements AI-based mathematical algorithms that incorporate and minimize or maximize all costs, materials, production, distribution, overhead as well as price. Implemented algorithms could be used to calculate a maximum profit for a given set of costs and a chosen price e.g.

All this could be combined as well as with simulation modeling which requires a number of simulated scenarios to choose the best option and target.

Decision Support System

Using artificial intelligence, DSS learns from previous cases and improves with time, providing a more efficient decision-making mechanism that is continuously evolving. DSS allows human agents to focus more on their soft skills and quality of the interaction, and less on scripts and manuals.

Our team has developed a few systems where complicated scripts are used to identify and troubleshoot issues and guide customers through to resolution. The process requires possession of a large dataset which is difficult for the most highly trained agent to remember.

Robotic Process Automation

Artificial Intelligence (AI) models can be inserted into Robotic Process Automation (RPA) workflows to perform machine perception tasks, like image recognition e.g. Tasks that by the human brain can be performed in seconds, whose output may be plugged into a large flow of business and process logic.

RPA is considered by many of our customers as a needed element of the digital transformation era. When RPA is used along with AI efficiency improvement can be achieved.

Top 3 Benefits of AI for Business

Automation

There can be no different starting point to listing key benefits of Artificial Intelligence than automation. Yes, it is not the most “cinematic” application of AI, there are no robots (even though they could be!), no Go gameplays, and creepy tracking algorithms, but automation is the ultimate and most common reason to reach out for AI.

It significantly influences the communications, transportation, consumer products, and service industries, leading to higher production rates and increased productivity in these sectors. Also, it enables more efficient raw materials utilization, product quality improvement, lead times reduction, and safety increment.

Given all of that, it is easy to get disturbed that AI will steal our jobs, but it would be massive simplifications. Artificial Intelligence will change how we handle the repetitive tasks involving data processing but also help free resources that can be used for more high-level, strategic things.

Data-grounded Decision Making

It is also one of the main goals of AI was designed. As this technology can coordinate data delivery, analyze trends, check data consistency, and provide predictions, including even uncertain events, it can significantly support companies to improve their decision-making processes.

With AI solutions, businesses can rely on unbiased data and use them in practice.

Supercharged Customer Experience

Customer Experience is the term typically related to retail, but – in the online era, when almost every company shifts their services to the internet, it seems a bit outdated. Today, nearly every user is (or can be) a customer regardless of whether we deal with finance, insurance, travel, or hospitality industries. AI-powered solutions help these businesses to respond to customer queries and grievances in real-time and address the situations more efficiently.

In that case, chatbots that use conversational AI combined with Natural Language Processing technology can generate highly personalized messages while reducing the strain on the customer service staff.

Benefits of AI in Software Development

As we mentioned above, AI benefits fit any industry and – as such – can sound too general. To narrow the issue down, we will focus on one specific industry: software development, in which AI caused a considerable revamping.

AI enables developers and QA specialists to be more efficient, helping them make quicker progress, creating more reliable and advanced programs, monitoring and understanding how data flows in their system. All of this makes the software development process much more efficient.

Bugs & Errors Detection

Traditionally, where there was no dedicated technology, testing and development software involved a lot of tedious and repetitive work that had to be done to detect bugs in software. Scanning and investigating the code, line by line, was quite challenging and made the process extremely time-consuming and error-prone.

With Machine Learning models implemented in QA processes, developers and testers can predict and prevent errors automatically by searching through the codebase.

Strategic decision-making

The software development process involves establishing priorities and highlighting crucial features that must be implemented first. Artificial Intelligence algorithms can support decisions about what business factors must be included while planning software development. AI can analyze existing applications’ performance and help reduce the risk of bad choices.

Enhanced Data Security

Data security is crucial, especially while working with clients’ software development, and any data breach can cause severe financial implications. With AI, the system can gather data from network sensors and internal and external software and easily detect violations.

Smooth deployment processes

AI in software development helps to increase efficiency while deployment activities related to software development, when developers upgrade programs or applications to the latest version. Software developers can use AI-driven applications to upgrade their programs.

AI-models features

Any software, regardless of its purpose, type of end-users, and complexity, uses data and – as such – can be enhanced or scaled by harnessing AI models to analyze them quickly and more efficiently.

With AI in software development, companies creating IoT, eCommerce systems, streaming platforms, or any online services can add the “wisdom” from data analysis to their products.

Enhanced customer experience

AI in software development enables businesses to keep up with their customers’ needs, respond to their queries and grievances quickly, and address the issues more efficiently with – for example – chatbots using Natural Language Processing technology.

Personalization

Artificial I solutions can also suggest much more personalized product offerings and embrace up- and cross-selling activities in retail. AI and IoT help optimize product placement in-store and run more effective ad campaigns. AI drives predictive analysis that can prevent inventory shortages.

Learn More About AI in Software Development

Our AI software developers and architects are always happy to share their knowledge of the field, as well as experience in AI solutions and software development.

In their articles, you can find useful information and guidance on what important aspects you need to consider while implementing Artificial Intelligence (AI) solutions to your business and building software and products based on AI. From showing particular implementation to descriptions of how AI software development is different from the traditional processes, you can learn more and make an informed decision.

Check out our insights about AI software and product building.

AI and Machine Learning In Gaming

Let’s analyze some of the most effective AI solutions which can boost business outcomes in the gaming sector.

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Image Recognition and Text Mining in Retail (case study)

We helped one of the global retail companies to optimize online ad spendings by using text mining.

We also found a solution to increase the effectiveness of the operational activities (process automation) by using image recognition and computer vision.

Advanced AI algorithms were deployed to minimize costs and automate workflow thanks to Machine Learning.

Read the case

Why should you work with Addepto?

How we work?

We help particular teams inside the company come up with ways of solving their problems using AI technologies and software. They provide context and examples of how it can work.

After deeply analyzing a company’s goals and structure, we also suggest our own ideas on how AI could be implemented with the highest ROI. It gives a clear overview of what benefits advanced AI solutions can bring to your company.

1. Discover and feasibility study
2. Building a prototype
3. Integration into existing system or product building
4. Production deployment

Technologies we use in developing AI solutions

Python is programming; a general-purpose language often used to build websites and software, automate tasks, and conduct data analysis.

Amazon Kinesis is an Amazon Web Service (AWS) for processing big data in real time, processing the vast amount of streaming data from multiple sources.

R is an open-source scripting language for predictive analytics and data visualization.

MongoDB is an open-source NoSQL database management program that manages document-oriented information and stores or retrieves information.

PyTorch is an open-source Machine Learning framework that accelerates the path from research prototyping to production deployment.

TensorFlow is a Python-friendly open-source library that fastens the Machine Learning models’ deployment.

Apache Hadoop is a framework that enables developers to distribute the processing of large data sets across clusters using simple programming models.

PySpark is the Python API for Apache Spark.

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